Variations in Performance and Scalability when Migrating n-tier Applications to Different Clouds

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1 Variations in Performance and Scalability when Migrating n-tier Applications to Different Clouds Deepal Jayasinghe, Simon Malkowski, Qingyang Wang, Jack Li, Pengcheng Xiong, Calton Pu

2 Outline Motivation Experiment setup Results on Emulab/ Open Cirrus Results on EC2 Horizontal scalability Vertical Scalability Issue 1 : Multi-threading overhead Issue 2 : Network driver overhead Conclusion

3 Motivation Clouds are much popular, but not a mature technology. More experimental studies are needed to better understand them. N-Tier applications are complex and migrating them to clouds is a non-trivial task. We analyzed the performance and scalability when migrating n-tier applications from a traditional datacenter to an Infrastructure as a Service (IaaS) cloud.

4 Experiment Setup RUBBoS benchmark Bulletin board system like Slashdot (www.slashdot.org) Typical 3-tier or 4-tier architecture Two types of workload Browsing only Read/Write mix 24 web interactions MySQL Cluster Middleware for database scale-out Multi-master In-memory RUBBoS Deployment Topology with MySQL Cluster

5 Experiment Environment - Emulab Emulab (http://www.emulab.net) Relatively modest testbed originally for network research Virtual network & physical machines (not VM) Hardware Server type Processor Memory Network Disk Specifications PC3000 in Emulab Xeon 3GHz 64bit 2GB 1Gbps 2 x 146GB 10,000rpm

6 Experiment Environment Open Cirrus Open Cirrus (https://opencirrus.org/) Open cloud-computing research testbed Designed to support research into the design, provisioning, and management of services at a global, multi-datacenter scale. Hardware Server type Processor Memory Network Specifications X GHz (Quad Core) 7.5 GB InfiniBand

7 Experiment Environment Amazon EC2 Amazon EC2 (http://aws.amazon.com/ec2/) An Elastic Compute Cloud that provides resizable compute capacity in the cloud. It is designed to make web-scale computing easier for developers. Node Type CPU Memory Platform Price/Hour Small 1 EC2 Unit GB 32 bit $ Large 4 EC2 Unit 7.5 GB 64 bit $ 0.34 Ex-Large 8 EC2 Unit 15 GB 64 bit $ 0.68 Cluster 33.5 EC2 Unit 23 GB 64 bit $ : EC2 Unit = GHz 2007 Opteron or 2007 Xeon processor

8 Software Settings Function Software Web server Apache Application server Apache Tomcat DB clustering middleware MySQL Cluster a Java Sun jdk1.6.0_14 Operating system FC4 / FC8 System Monitor dstat

9 Summary of Experiments Automated experiment management approach (Elba 1 ) Type Emulab Open Cirrus Amazon EC2 Experiments Node Configurations Data points M 2.3 M 672 M 1:

10 Notation We use the notation #W-#A-#S-#D-p #W Number of Web server (all experiments in this paper with one Web server) #A Number of Application servers #S Number of SQL nodes #D Number of Data nodes p Platforms (em- for Emulab, oc for Open Cirrus, ec2- for EC2) em Emulab configuration with 1-Apache, 2-Tomcats, 2-SQL nodes and 2-Data nodes

11 Throughput (Req/Sec) Performance on Emulab Improvement Improvement em em em # Users

12 Throughput (Req/Sec) Performance on Open Cirrus Improvement 750 Improvement oc oc oc # Users

13 Throughput (Req/Sec) Performance on EC Degradation Degradation ec ec ec2 100 On Large instances # Users

14 CPU Utilization ( ) EC2 Emulab Tomcat MySQL Data Node

15 Throughput (Req/Sec) Vertical Scalability on EC Improvement Improvement Improvement small large exlarge cluster # Users

16 Summary Emulab and Open Cirrus show better horizontal scalability EC2 show good vertical scalability, but not better horizontal scalability Our analysis resulted in two findings: Multi-threading overhead Network driver overhead

17 Multi-Threading Overhead

18 End-to-End Response Time Client End-to-End Web Server End-to-End

19 Reesponse Time (s) Differences in Response Time Web-Server RUBBoS Client Time differences # Users

20 Time per switchs (micro second) Context Switching (using LMBench) Emulab EC # Threads

21 Context Switches Number of Context Switches EC2 Emulab # Users

22 CPU Percentage [%] CPU Percentage Emulab EC # Users

23 Issues and Solution Overall throughput and number of context switches are related But, in EC2 we get less switches and similar overhead as Emulab When the number of threads is higher the application become unstable in EC2 Solutions: Rent many instances Re-write the application with less number of threads

24 Response Time [s] With our Solution Web-Server RUBBoS Client RUBBoS Client with reduced threads Improvement # Users

25 Throughput [Req/Sec] Solution - Improvements Improvement Orginal client Client-with reduced threads # Users

26 Network Driver Overhead

27 Queue Size (B) Data Node Send Queue em ec # Users

28 Round Trip time (ms) Ping-Pong Time without a Load emulab EC Duration

29 Round Trip time (ms) Ping-Pong with a Load emulab EC Duration

30 Solution Use network friendly database middleware Reduce the pressure on the network Evaluated C-JDBC, an open source database middleware Performed well and showed a very good scalability Reduce the network traffic significantly

31 Throughput [Req/Sec] C-JDBC vs. MySQL Cluster Performance CJDBC MySQL # Users

32 Data Transfered [MB/s] C-JDBC vs. MySQL Cluster Network Traffic C-JDBC MYSQL # Users

33 Conclusion & Future works Studied the performance and scalability variations when migrating n-tier applications to clouds. Our results show, that cloud are new and need more experimental studies to better understand them. More specifically, application re-design is needed to handle cloud challenges. Future works Extend our analysis into other clouds (e.g., Wipro) Micro level study to dig deep into observe phenomena With other database monument systems (e.g., Oracle, DB2)

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